Sparse coding of hyperspectral imagery using online learning. - Irem Ülkü; Behcet Ugur Töreyin (Signal Image Video Process., 2015)

Large-scale hyperspectral image compression via sparse representations based on online learning. - Irem Ülkü; Ersin Kizgut (Int. J. Appl. Math. Comput. Sci., 2018)

Comparison of single channel indices for U-Net based segmentation of vegetation in satellite images. - Irem Ülkü; Panagiotis Barmpoutis; Tania Stathaki; Erdem Akagündüz (ICMV, 2019)

Lossy Compressive Sensing Based on Online Dictionary Learning. - Irem Ülkü; Ersin Kizgut (Comput. Informatics, 2019)

Semantic segmentation of crop areas in remote sensing imagery using spectral indices and multiple channels. - Irem Ülkü; Erdem Akagündüz (ICMV, 2022)

A Survey on Deep Learning-based Architectures for Semantic Segmentation on 2D Images. - Irem Ülkü; Erdem Akagündüz (Appl. Artif. Intell., 2022)

Deep Semantic Segmentation of Trees Using Multispectral Images. - Irem Ülkü; Erdem Akagündüz; Pedram Ghamisi (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022)

Near-Infrared and Low-Rank Adaptation of Vision Transformers in Remote Sensing. - Irem Ülkü; Ö. Özgür Tanriöver; Erdem Akagündüz (CoRR, 2024)

LoRA-NIR: Low-Rank Adaptation of Vision Transformers for Remote Sensing With Near-Infrared Imagery. - Irem Ülkü; Ö. Özgür Tanriöver; Erdem Akagündüz (IEEE Geosci. Remote. Sens. Lett., 2024)

ResLMFFNet: a real-time semantic segmentation network for precision agriculture. - Irem Ülkü (J. Real Time Image Process., 2024)